An automated, fixed-location, time lapse camera system was developed as an alternative to monitoring geological processes with lidar or ground-based interferometric synthetic-aperture radar (GB-InSAR). The camera system was designed to detect fragmental rockfalls and pre-failure deformation at rock slopes. It was implemented at a site along interstate I70 near Idaho Springs, Colorado. The camera system consists of five digital single-lens reflex (DSLR) cameras which collect photographs of the rock slope daily and automatically upload them to a server for processing. Structure from motion (SfM) photogrammetry workflows were optimized to be used without ground control. An automated change detection pipeline registers the point clouds with scale adjustment and filters vegetation. The results show that if a fixed pre-calibration of internal camera parameters is used, an accuracy close to that obtained using ground control points can be achieved. Over the study period between March 19, 2018 and June 24, 2019, a level of detection between 0.02 to 0.03 m was consistently achieved, and over 50 rockfalls between 0.003 to 0.1 m3 were detected at the study site. The design of the system is fit for purpose in terms of its ground resolution size and accuracy and can be adapted to monitor a wide range of geological and geomorphic processes at a variety of time scales.
This paper demonstrates the application of the Gaussianmixture model technique for separation of phase centres in an area containing the aggregate of scattering centres at multiple distances from the SAR sensor. Typically co-polar phase differences have a unimodal gaussian distribution over a diffuse scatterer with high interchannel coherence. This paper shows that in special conditions the phase difference distribution is multimodal with stable mean values and standard deviation over time, indicating correspondence to the separation of coherent scattering centres over the target area.
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